Article

Quantitative gait dysfunction and risk of cognitive decline and dementia

Department of Neurology, Albert Einstein College of Medicine, 1165 Morris Park Avenue, Room 338, Bronx, New York 10461, USA.
Journal of neurology, neurosurgery, and psychiatry (Impact Factor: 6.81). 10/2007; 78(9):929-35. DOI: 10.1136/jnnp.2006.106914
Source: PubMed

ABSTRACT

Identifying quantitative gait markers of preclinical dementia may lead to new insights into early disease stages, improve diagnostic assessments and identify new preventive strategies.
To examine the relationship of quantitative gait parameters to decline in specific cognitive domains as well as the risk of developing dementia in older adults.
We conducted a prospective cohort study nested within a community based ageing study. Of the 427 subjects aged 70 years and older with quantitative gait assessments, 399 were dementia-free at baseline.
Over 5 years of follow-up (median 2 years), 33 subjects developed dementia. Factor analysis was used to reduce eight baseline quantitative gait parameters to three independent factors representing pace, rhythm and variability. In linear models, a 1 point increase on the rhythm factor was associated with further memory decline (by 107%), whereas the pace factor was associated with decline on executive function measured by the digit symbol substitution (by 29%) and letter fluency (by 92%) tests. In Cox models adjusted for age, sex and education, a 1 point increase on baseline rhythm (hazard ratio (HR) 1.48; 95% CI 1.03 to 2.14) and variability factor scores (HR 1.37; 95% CI 1.05 to 1.78) was associated with increased risk of dementia. The pace factor predicted the risk of developing vascular dementia (HR 1.60; 95% CI 1.06 to 2.41).
Our findings indicate that quantitative gait measures predict future risk of cognitive decline and dementia in initially non-demented older adults.

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    • "A more comprehensive gait analysis that moves beyond gait speed, including dynamic metrics of gait (e.g., gait smoothness, regularity, stability; [Lamoth et al., 2011; Ijmker and Lamoth, 2012; Brach et al., 2010]), could increase the specificity of the relationship with future cognitive decline. For example, studies included in the present review showed that pace, rhythm and variability of gait were uniquely related to decline in specific cognitive functions and types of dementia (Verghese et al., 2007). Because comorbidities and other conditions (e.g., low back pain, osteoarthritis, medication) and their detrimental effects on gait speed are common in older adults, dynamic metrics of gait compared with gait velocity might be more sensitive to predict cognitive decline. "
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    • "As in our previous studies, global health status (GHS; range 0– 10) was obtained from dichotomous rating (presence or absence) of medical illnesses including: diabetes, chronic heart failure, arthritis, hypertension, depression, stroke, PD, chronic obstructive pulmonary disease, angina, and myocardial infarction (Verghese et al., 2007). Global cognitive status was assessed using the RBANS total score. "
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    • "Identifying and grouping different walking conditions is extremely important in the generation and statistical analysis of representative data given that they will utilize different joint and foot kinematics . Without this function, it is not possible to effectively compare across participants (as in this study) or to longitudinally track individuals for the early identification/screening of neuro-musculoskeletal injury or cognitive decline [1], [2]. Currently, no systems appear to facilitate this. "
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